Dynamic proofs of retrievability with low server storage

Proofs of Retrievability (PoRs) are protocols which allow a client to store data remotely and to efficiently ensure, via audits, that the entirety of that data is still intact. A dynamic PoR system also supports efficient retrieval and update of any small portion of the data. We propose new, simple protocols for dynamic PoR that are designed for practical efficiency, trading decreased persistent storage for increased server computation, and show in fact that this tradeoff is inherent via a lower bound proof of time-space for any PoR scheme. Notably, ours is the first dynamic PoR which does not require any special encoding of the data stored on the server, meaning it can be trivially composed with any database service or with existing techniques for encryption or redundancy. Our implementation and deployment on Google Cloud Platform demonstrates our solution is scalable: for example, auditing a 1TB file takes just less than 5 minutes and costs less than $0.08 USD. We also present several further enhancements, reducing the amount of client storage, or the communication bandwidth, or allowing public verifiability, wherein any untrusted third party may conduct an audit

The data integrity problem and multi-layered document integrity

Data integrity is a fundamental aspect of computer security that has attracted much interest in recent decades. Despite a general consensus for the meaning of the problem, the lack of a formal definition has led to spurious claims such as "tamper proof", "prevent tampering", and "tamper protection", which are all misleading in the absence of a formal definition. Ashman recently proposed a new approach for protecting the integrity of a document that claims the ability to detect, locate, and correct tampering. If determining integrity is only part of the problem, then a more general notion of data integrity is needed. Furthermore, in the presence of a persistent tamperer, the problem is more concerned with maintaining and proving the integrity of data, rather than determining it. This thesis introduces a formal model for the more general notion of data integrity by providing a formal problem semantics for its sub-problems: detection, location, correction, and prevention. The model is used to reason about the structure of the data integrity problem and to prove some fundamental results concerning the security and existence of schemes that attempt to solve these sub-problems. Ashman's original multi-layered document integrity (MLDI) paper [1] is critically evaluated, and several issues are highlighted. These issues are investigated in detail, and a series of algorithms are developed to present the MLDI schemes. Several factors that determine the feasibility of Ashman's approach are identified in order to prove certain theoretical results concerning the efficacy of MLDI schemes

The data integrity problem and multi-layered document integrity

Data integrity is a fundamental aspect of computer security that has attracted much interest in recent decades. Despite a general consensus for the meaning of the problem, the lack of a formal definition has led to spurious claims such as "tamper proof", "prevent tampering", and "tamper protection", which are all misleading in the absence of a formal definition. Ashman recently proposed a new approach for protecting the integrity of a document that claims the ability to detect, locate, and correct tampering. If determining integrity is only part of the problem, then a more general notion of data integrity is needed. Furthermore, in the presence of a persistent tamperer, the problem is more concerned with maintaining and proving the integrity of data, rather than determining it. This thesis introduces a formal model for the more general notion of data integrity by providing a formal problem semantics for its sub-problems: detection, location, correction, and prevention. The model is used to reason about the structure of the data integrity problem and to prove some fundamental results concerning the security and existence of schemes that attempt to solve these sub-problems. Ashman's original multi-layered document integrity (MLDI) paper [1] is critically evaluated, and several issues are highlighted. These issues are investigated in detail, and a series of algorithms are developed to present the MLDI schemes. Several factors that determine the feasibility of Ashman's approach are identified in order to prove certain theoretical results concerning the efficacy of MLDI schemes

Identifying and Preventing Large-scale Internet Abuse

The widespread access to the Internet and the ubiquity of web-based services make it easy to communicate and interact globally. Unfortunately, the software and protocols implementing the functionality of these services are often vulnerable to attacks. In turn, an attacker can exploit them to compromise, take over, and abuse the services for her own nefarious purposes. In this dissertation, we aim to better understand such attacks, and we develop methods and algorithms to detect and prevent them, which we evaluate on large-scale datasets.First, we detail Meerkat, a system to detect a visible way in which websites are being compromised, namely website defacements. They can inflict significant harm on the websites’ operators through the loss of sales, the loss in reputation, or because of legal ramifications. Meerkat requires no prior knowledge about the websites’ content or their structure, but only the Uniform Resource Identifier (URI) at which they can be reached. By design, Meerkat mimics how a human analyst decides if a website was defaced when viewing it in a browser, by using computer vision techniques. Thus, it tackles the problem of detecting website defacements through their attention-seeking nature, their goal and purpose, rather than code or data artifacts that they might exhibit. In turn, it is much harder for an attacker to evade our system, as she needs to change her modus operandi. When Meerkat detects a website as defaced, the website can automatically be put into maintenance mode or restored to a known good state.An attacker, however, is not limited to abuse a compromised website in a way that is visible to the website’s visitors. Instead, she can misuse the website to infect its visitors with malicious software (malware). Although malware is well studied, identifying malicious websites remains a major challenge in today’s Internet. Second, we introduce Delta, a novel, purely static analysis approach that extracts change-related features between two versions of the same website, uses machine learning to derive a model of website changes, detects if an introduced change was malicious or benign, identifies the underlying infection vector based on clustering, and generates an identifying signature. Furthermore, due to the way Delta clusters campaigns, it can uncover infection campaigns that leverage specific vulnerable applications as a distribution channel, and it can greatly reduce the human labor necessary to uncover the application responsible for a service’s compromise.Third, we investigate the practicality and impact of domain takeover attacks, which an attacker can similarly abuse to spread misinformation or malware, and we present a defense on how such takeover attacks can be rendered toothless. Specifically, the new elasticity of Internet resources, in particular Internet protocol (IP) addresses in the context of Infrastructure-as-a-Service cloud service providers, combined with previously made protocol assumptions can lead to security issues. In Cloud Strife, we show that this dynamic component paired with recent developments in trust-based ecosystems (e.g., Transport Layer Security (TLS) certificates) creates so far unknown attack vectors. For example, a substantial number of stale domain name system (DNS) records points to readily available IP addresses in clouds, yet, they are still actively attempted to be accessed. Often, these records belong to discontinued services that were previously hosted in the cloud. We demonstrate that it is practical, and time and cost-efficient for attackers to allocate the IP addresses to which stale DNS records point. Further considering the ubiquity of domain validation in trust ecosystems, an attacker can impersonate the service by obtaining and using a valid certificate that is trusted by all major operating systems and browsers, which severely increases the attackers’ capabilities. The attacker can then also exploit residual trust in the domain name for phishing, receiving and sending emails, or possibly distributing code to clients that load remote code from the domain (e.g., loading of native code by mobile apps, or JavaScript libraries by websites). To prevent such attacks, we introduce a new authentication method for trust-based domain validation that mitigates staleness issues without incurring additional certificate requester effort by incorporating existing trust into the validation process.Finally, the analyses of Delta, Meerkat, and Cloud Strife have made use of large-scale measurements to assess our approaches’ impact and viability. Indeed, security research in general has made extensive use of exhaustive Internet-wide scans over the recent years, as they can provide significant insights into the state of security of the Internet (e.g., if classes of devices are behaving maliciously, or if they might be insecure and could turn malicious in an instant). However, the address space of the Internet’s core addressing protocol (Internet Protocol version 4; IPv4) is exhausted, and a migration to its successor (Internet Protocol version 6; IPv6), the only accepted long-term solution, is inevitable. In turn, to better understand the security of devices connected to the Internet, in particular Internet of Things devices, it is imperative to include IPv6 addresses in security evaluations and scans. Unfortunately, it is practically infeasible to iterate through the entire IPv6 address space, as it is 296 times larger than the IPv4 address space. Without enumerating hosts prior to scanning, we will be unable to retain visibility into the overall security of Internet-connected devices in the future, and we will be unable to detect and prevent their abuse or compromise. To mitigate this blind spot, we introduce a novel technique to enumerate part of the IPv6 address space by walking DNSSEC-signed IPv6 reverse zones. We show (i) that enumerating active IPv6 hosts is practical without a preferential network position contrary to common belief, (ii) that the security of active IPv6 hosts is currently still lagging behind the security state of IPv4 hosts, and (iii) that unintended default IPv6 connectivity is a major security issue

A Taxonomy of Blockchain Technologies: Principles of Identification and Classification

A comparative study across the most widely known blockchain technologies is conducted with a bottom-up approach. Blockchains are deconstructed into their building blocks. Each building block is then hierarchically classified into main and subcomponents. Then, varieties of the subcomponents are identified and compared. A taxonomy tree is used to summarise the study and provide a navigation tool across different blockchain architectural configurations

A Framework for the Systematic Evaluation of Malware Forensic Tools

Following a series of high profile miscarriages of justice linked to questionable expert evidence, the post of the Forensic Science Regulator was created in 2008 with a remit to improve the standard of practitioner competences and forensic procedures. It has since moved to incorporate a greater level of scientific practice in these areas, as used in the production of expert evidence submitted to the UK Criminal Justice System. Accreditation to their codes of practice and conduct will become mandatory for all forensic practitioners by October 2017. A variety of challenges with expert evidence are explored and linked to a lack of a scientific methodology underpinning the processes followed. In particular, the research focuses upon investigations where malicious software (‘malware’) has been identified. A framework, called the ‘Malware Analysis Tool Evaluation Framework’ (MATEF), has been developed to address this lack of methodology to evaluate software tools used during investigations involving malware. A prototype implementation of the framework was used to evaluate two tools against a population of over 350,000 samples of malware. Analysis of the findings indicated that the choice of tool could impact on the number of artefacts observed in malware forensic investigations as well as identifying the optimal execution time for a given tool when observing malware artefacts. Three different measures were used to evaluate the framework. The first of these evaluated the framework against the requirements and determined that these were largely met. Where the requirements were not met these are attributed to matters either outside scope or the fledgling nature of the research. Another measure used to evaluate the framework was to consider its performance in terms of speed and resource utilisation. This identified scope for improvement in terms of the time to complete a test and the need for more economical use of disk space. Finally, the framework provides a scientific means to evaluate malware analysis tools, hence addressing the Research Question subject to the level at which ground truth is established. A number of contributions are produced as the output of this work. First there is confirmation for the case for a lack of trusted practice in the field of malware forensics. Second, the MATEF itself, as it facilitates the production of empirical evidence of a tool’s ability to detect malware artefacts. A third contribution is a set of requirements for establishing trusted practice in the use of malware artefact detection tools. Finally, empirical evidence that supports both the notion that the choice of tool can impact on the number of artefacts observed in malware forensic investigations as well as identifying the optimal execution time for a given tool when observing malware artefacts

Advances in Information Security and Privacy

With the recent pandemic emergency, many people are spending their days in smart working and have increased their use of digital resources for both work and entertainment. The result is that the amount of digital information handled online is dramatically increased, and we can observe a significant increase in the number of attacks, breaches, and hacks. This Special Issue aims to establish the state of the art in protecting information by mitigating information risks. This objective is reached by presenting both surveys on specific topics and original approaches and solutions to specific problems. In total, 16 papers have been published in this Special Issue